doc updates (#1639)

---------

Co-authored-by: vbarda <vadym@langchain.dev>

examples/multi_agent/agent_supervisor.ipynb

@@ -5,7 +5,7 @@
    "id": "a3e3ebc4-57af-4fe4-bdd3-36aff67bf276",
    "metadata": {},
    "source": [
-    "## Agent Supervisor\n",
+    "# Agent Supervisor\n",
     "\n",
     "The [previous example](multi-agent-collaboration.ipynb) routed messages automatically based on the output of the initial researcher agent.\n",
     "\n",
@@ -17,7 +17,9 @@
     "\n",
     "To simplify the code in each agent node, we will use the AgentExecutor class from LangChain. This and other \"advanced agent\" notebooks are designed to show how you can implement certain design patterns in LangGraph. If the pattern suits your needs, we recommend combining it with some of the other fundamental patterns described elsewhere in the docs for best performance.\n",
     "\n",
-    "Before we build, let's configure our environment:"
+    "## Setup\n",
+    "\n",
+    "First, let's install required packages and set our API keys"
    ]
   },
   {
@@ -48,12 +50,20 @@
     "\n",
     "\n",
     "_set_if_undefined(\"OPENAI_API_KEY\")\n",
-    "_set_if_undefined(\"LANGCHAIN_API_KEY\")\n",
-    "_set_if_undefined(\"TAVILY_API_KEY\")\n",
-    "\n",
-    "# Optional, add tracing in LangSmith\n",
-    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
-    "os.environ[\"LANGCHAIN_PROJECT\"] = \"Multi-agent Collaboration\""
+    "_set_if_undefined(\"TAVILY_API_KEY\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be85e3ad",
+   "metadata": {},
+   "source": [
+    "<div class=\"admonition tip\">\n",
+    "    <p class=\"admonition-title\">Set up <a href=\"https://smith.langchain.com\">LangSmith</a> for LangGraph development</p>\n",
+    "    <p style=\"padding-top: 5px;\">\n",
+    "        Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started <a href=\"https://docs.smith.langchain.com\">here</a>. \n",
+    "    </p>\n",
+    "</div>    "
    ]
   },
   {

examples/multi_agent/hierarchical_agent_teams.ipynb

@@ -5,7 +5,7 @@
    "id": "a3e3ebc4-57af-4fe4-bdd3-36aff67bf276",
    "metadata": {},
    "source": [
-    "## Hierarchical Agent Teams\n",
+    "# Hierarchical Agent Teams\n",
     "\n",
     "In our previous example ([Agent Supervisor](./agent_supervisor.ipynb)), we introduced the concept of a single supervisor node to route work between different worker nodes.\n",
     "\n",
@@ -26,7 +26,9 @@
     "3. Create and define each team (web research + doc writing)\n",
     "4. Compose everything together.\n",
     "\n",
-    "But before all of that, some setup:"
+    "## Setup\n",
+    "\n",
+    "First, let's install our required packages and set our API keys"
    ]
   },
   {
@@ -41,8 +43,8 @@
    },
    "outputs": [],
    "source": [
-    "# %%capture --no-stderr\n",
-    "# %pip install -U langgraph langchain langchain_openai langchain_experimental"
+    "%% capture --no-stderr\n",
+    "%pip install -U langgraph langchain langchain_openai langchain_experimental"
    ]
   },
   {
@@ -67,13 +69,20 @@
     "\n",
     "\n",
     "_set_if_undefined(\"OPENAI_API_KEY\")\n",
-    "_set_if_undefined(\"LANGCHAIN_API_KEY\")\n",
-    "_set_if_undefined(\"TAVILY_API_KEY\")\n",
-    "\n",
-    "# Optional, add tracing in LangSmith.\n",
-    "# This will help you visualize and debug the control flow\n",
-    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
-    "os.environ[\"LANGCHAIN_PROJECT\"] = \"Multi-agent Collaboration\""
+    "_set_if_undefined(\"TAVILY_API_KEY\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "04fdd0a3",
+   "metadata": {},
+   "source": [
+    "<div class=\"admonition tip\">\n",
+    "    <p class=\"admonition-title\">Set up <a href=\"https://smith.langchain.com\">LangSmith</a> for LangGraph development</p>\n",
+    "    <p style=\"padding-top: 5px;\">\n",
+    "        Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started <a href=\"https://docs.smith.langchain.com\">here</a>. \n",
+    "    </p>\n",
+    "</div>    "
    ]
   },
   {

examples/multi_agent/multi-agent-collaboration.ipynb

@@ -17,7 +17,11 @@
     "\n",
     "![multi_agent diagram](./img/simple_multi_agent_diagram.png)\n",
     "\n",
-    "Before we get started, a quick note: this and other multi-agent notebooks are designed to show _how_ you can implement certain design patterns in LangGraph. If the pattern suits your needs, we recommend combining it with some of the other fundamental patterns described elsewhere in the docs for best performance."
+    "Before we get started, a quick note: this and other multi-agent notebooks are designed to show _how_ you can implement certain design patterns in LangGraph. If the pattern suits your needs, we recommend combining it with some of the other fundamental patterns described elsewhere in the docs for best performance.\n",
+    "\n",
+    "## Setup\n",
+    "\n",
+    "First, let's install our required packages and set our API keys:"
    ]
   },
   {
@@ -48,12 +52,20 @@
     "\n",
     "\n",
     "_set_if_undefined(\"OPENAI_API_KEY\")\n",
-    "_set_if_undefined(\"LANGCHAIN_API_KEY\")\n",
-    "_set_if_undefined(\"TAVILY_API_KEY\")\n",
-    "\n",
-    "# Optional, add tracing in LangSmith\n",
-    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
-    "os.environ[\"LANGCHAIN_PROJECT\"] = \"Multi-agent Collaboration\""
+    "_set_if_undefined(\"TAVILY_API_KEY\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ab5cea6d",
+   "metadata": {},
+   "source": [
+    "<div class=\"admonition tip\">\n",
+    "    <p class=\"admonition-title\">Set up <a href=\"https://smith.langchain.com\">LangSmith</a> for LangGraph development</p>\n",
+    "    <p style=\"padding-top: 5px;\">\n",
+    "        Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started <a href=\"https://docs.smith.langchain.com\">here</a>. \n",
+    "    </p>\n",
+    "</div>    "
    ]
   },
   {